Abstract
We present an indexing and retrieval system of historic art images based on fuzzy shape similarity. The system is composed of three principal components: object annotation, object shape indexing, and query/retrieval. The object annotation in database images is done manually offline. The object shape indexing and retrieval, however, are done automatically. Annotated object shapes are indexed using an extended curvature scale space (CSS) descriptor suitable for concave and convex shapes. The query/retrieval of pertinent shapes from the database starts with a user drawing query (with a computer mouse or a pen) that is compared to entries in the database using a fuzzy similarity measure. The system is tested on a set of complex color and grey scale images of ancient documents, mosaics, and artifacts from the National Library of Tunisia, the National Archives of Tunisia, and a selection of Tunisian museums. The system’s recall and precision rates were 83% and 60%, respectively.
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References
National Library of Tunisia, http://www.bibliotheque.nat.tn
National Archive of Tunisia, http://www.archives.tn
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Maghrebi, W., Baccour, L., Khabou, M.A., Alimi, A.M. (2007). An Indexing and Retrieval System of Historic Art Images Based on Fuzzy Shape Similarity. In: Gelbukh, A., Kuri Morales, Á.F. (eds) MICAI 2007: Advances in Artificial Intelligence. MICAI 2007. Lecture Notes in Computer Science(), vol 4827. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76631-5_59
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DOI: https://doi.org/10.1007/978-3-540-76631-5_59
Publisher Name: Springer, Berlin, Heidelberg
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